Intra-household decision-making and child
health outcomes, evidence from Ghana
by
Sarah Akuoni
(Doctoral Research Student, Department of Economics, University of Sussex, Brighton )
PhD Conference, University of Sussex, Brighton 5th December 2014
OUTLINE
1. Motivation
2. Literature
3. Data and descriptive statistics
4. Empirical strategy
5. Results
6. Key findings
7. Conclusions and Next steps
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Motivation
The literature suggests a positive association between women’s
bargaining power (BP) and child welfare outcomes, including health
and nutrition.
(e.g. Lundberg, Pollak & Wales, 1997; Duflo, 2003; Doss 2006; Fafchamps, Kebede & Quisumbing,
2009).
But most studies use indirect measures of BP -(economic) proxies, as BP is
difficult to measure and context related;.
e.g. -non wage income transfers (Lundberg et al, 1997) ; assets (Doss, 2006, Fafchamps, Kebede and
Quisumbing, 2009)
Also while studies provide useful insights on importance of woman’s relative BP little attention is
given to balanced BP (except Basu, 2006)
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Motivation
Also, limited number of studies use direct measures of BP due to constraints
on data availability but different outcomes of interest
- (Freidberg and Webb, 2006: Dito, 2011; Lépine & Stobl, 2013)
This study uses a range of decision-making variables as ‘direct measures’
of BP; and examines their association across quintiles.
Focus on under 5 nutrition due to importance of early childhood nutrition
(Straus and Thomas, 1998; Schultz 1999; Alderman et al 2006; Hoddinott et al, 2011)
Data: Ghana DHS (2008) covers several domains of decisions and child
anthropometric data
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Literature
Child welfare outcomes linked to intra-household ‘bargaining’.
(McElroy & Horney, 1980; Manser & Brown, 1981; Browning & Chiappori, 1998)
-
-
heterogeneous preferences
importance of relative bargaining power (BP)
-
separate spheres in non cooperation (Lundberg and Pollak, 1993, Browning et al
2006)
key Assumption: Parents internalise children’s preferences
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Key Empirical Literature
– Relative education: mother’s with relatively better education than spouse
has a bigger impact on Daughter’s height (Thomas, 1994; Ghana )
– Non-wage income: increases through change in policy shifted spending
patterns in favour of children (Lundberg et al, 1997; UK Duflo, 2003; South Africa)
– Assets: Current asset ownership positively associated with child related
expenditure in Ghana (Doss, 2006)
• Also positive association with child nutrition in Ethiopia (Fafchamps et al, 2009)
– BP of mother positively associated with nutrition outcomes in Senegal;
relative ethnicity as IV. (Lépine & Stobl, 2013)
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Child Nutrition in Ghana
Malnutrition persists in southern Asia
and Sub-Saharan Africa.
1 out of 4 children under 5 are stunted, (UNICEF/WHO/The
World Bank, 2014)
33% of children under 5 mortality caused by
malnutrition. (UNCF 2011).
Ghana typifies the Sub-Saharan
situation (ICF Macro, 2010):
28% stunting; 14% wasting and 9% underweight
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Key Variables:
Data
Child anthropometric outcomes
Decision-making
Fifth round of Ghana Demographic Health Survey (DHS) 2008
- 11,778 households, nationally representative.
- 4, 916 women aged 15-49 and men 15-59 from half of households –
source of information on decision-making of spouses
–Valid anthropometric measures for 2,379 children from 1,742
households (208 single, 1,726 monogamous, and 445 polygamous)
2,360 linked with non-missing mother’s characteristics.
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Child Outcomes
• Z-scores of 3 child anthropometric measures: Height-for-age
(HFA), Weight-for-age (WFA), Weight-for-height (WFH)
• Z-scores (Zi) based on WHO (2006) world reference
population is:
𝑍𝑖 =
𝑋𝑖 − 𝑋
𝜎𝑥
(1)
Where:
Xi is the anthropometric measure for child i
𝑋 and 𝜎𝑥 are the median and standard deviation respectively of the WHO world
reference group for child is age.
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Child Outcomes
Variable
Obs
Mean
Std. Dev.
HFA
2379
-108
164
WFA
2379
-83
119
WFH
2379
-31
136
Stunted
2379
28
45
Severly Stunted
2379
10
29
underweight
2379
14
35
wasted
2379
9
29
Percentage :
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Kernel Densities of Z-scores
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Decision-making
Two measures:
1. Decisions related to separate domains – i.e. daily purchases, large purchases and
spending her income, spending his income, fertility, seeking healthcare for woman and
visits to her family.
Question : “Who has the final say on decisions about ………”
Responses:
1.
2.
3.
4.
Woman alone
Both decide
Husband alone
Other person
“Yes” = 1
“Yes” = 1
“Yes” = 1
“Yes” = 1
“No” = 0
“No” = 0
“No” = 0
“No” = 0
For each question, a binary variable Ri is defined. Such that :
Ri = 1 if “yes” and 0, otherwise.
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Decisions
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Decision-making variables
2. Decision Indices (𝐼𝑑 )
For each decision, (Di) is constructed such that:
Di = 1, if R1 or R2 =1;
Di = 0, otherwise
The decision index 𝐼𝑑 =
𝑛
𝑖=0 𝐷𝑖
Where:
n= number of decisions under consideration as below:
• Household: Decisions related to spending parents’ incomes (mother’s , father’s), household
purchases (daily, large purchases) and fertility
• 2. Mother’s welfare: Decisions related to mother’s welfare ( visits to family, seeking
healthcare)
• 3. All decisions
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Decision Indices
Woman’s involvement in household decision-making
Variable
Obs
Mean
Std. Dev.
Women’s involvement in decision-making (Percent) :
Large purchases
2171
55
50
Daily purchases
2171
75
42
Use of spouse’s earnings
2171
40
49
Use of woman's earnings
2171
63
46
Fertility
2171
76
42
Her health
2171
64
48
Her Mobility
2171
80
40
Household
2171
3.18
1.91
All
2171
4.62
1.91
Decision index:
Source: Author’s calculation from GHDHS5, 2008
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Empirical strategy
Informed by (UNICEF, 1990) framework and adaptation of Fafchamps,
Kebede & Quisumbing, 2009)
J
K
L
M
n
j 1
k 1
l 1
m 1
n 1
Z i    j HC j    k PCk    l CCl    m SCm    n DM n   i
Where:
–
–
–
–
–
–
Yij = Health outcome (HFA, WFA, WFH) of child i from hh j
HCj = vector of household characteristics
PCkj = vector of parental characteristics
CCij = vector of child characteristics
SCm = location specific controls
DMj= Decision-making variables
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Results:
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Results
BP Measure
HFA
WFA
WFH
All domain Index
2.77
5.66***
5.95***
HH decision index
5.45**
8.74***
8.15***
N
2360
2360
2360
R-Squared
0.16
0.13
0.1
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Results
BP Measure
HFA
WFA
Decisions about Daily Purchases and Child Nutrition
Woman
Both
18.78**
1.83
Man
3.91
-11.09
N
2360
2360
R-Squared
0.16
0.12
Decisions about freedom of mobility and Child Nutrition
Woman
Both
26.92***
13.76*
Man
17.5
-4.43
N
2360
2360
R-Squared
0.16
0.12
WFH
-10.4
-17.63*
2360
0.09
-1.58
-20.56**
2360
0.09
* p<0.10, ** p<0.05, *** p<0.01; Robust standard errors
clustered at the district level
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Results
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Results
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Results
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Key findings
• Better long term nutrition outcomes with joint parental decision
making on daily purchases and the woman’s freedom of mobility
• Worse child nutrition outcomes where men have the final say
relative to the woman having the final say
• For the malnourished children, a woman’s freedom of
mobility seems to matter most
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Conclusions
• That we only find significant results for decisions on daily purchases, and
freedom of mobility may suggest that child nutrition is not affected in the
same way by all bargaining domains or dimensions
• While a woman’s involvement in decision making is associated with better
nourished children, it would appear children are better off in the long term
in families where parents make joint decisions
• The multidimensionality of BP needs to be considered in policies aimed at
altering household welfare allocation.
•
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Thank you for your attention!
Key variables: outcomes
The study employs the following three measures of nutrition, z-scores of
child anthropometric measures :
 Height-for-age (HFA) measures effects of long term malnutrition;
• HFA <2 sd’s implies child is stunted, <3 sd’s implies severe stunting
 Weight-for-age (WFA) measures effects of short term malnutrition;
• WFA<2 sd’s implies child is underweight , <3 sd’s implies severe stunting
 Weight-for-height (WFH) measures a combination of long and short term
nutrition;
• WFH <2 sd’s implies child is wasted)
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Literature
Analytical framework for modelling child health outcomes: insert hyperlink
(UNICEF, 1990).
Empirical studies, use child, parent, household and community factors:
(examples: Haddad & Hoddinott 1994, Duflo 2003, Fafchamps, Kebede &
Quisumbing, 2009)
1.
2.
3.
4.
Child characteristics –current age, sex, birth weight, birth order. Some studies (e.g. Fotso, 2007) include
antenatal care, place of delivery, immunisation status birth interval and duration of breast feeding,
whether the child suffered illness/disease
Parent characteristics: Primarily Mother’s age, education, measures of mother’s nutritional status ,
employment/occupation; father’s age, education, occupation
Household characteristics: household wealth, nature of dwelling, access to water and sanitation, size and
composition, sex of head
Community: Geographical location (e.g. rural urban); cultural norms (ethnicity) accessibility of health
facility among others
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Next steps
• Use a Heckman 2 step approach to first
model survival then child nutrition
• Pooling DHS4 and DHS5 to increase N
• Exploring the polygamy story further
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